Aims. The self-accelerating braneworld model (DGP) appears to provide a simple alternative to the standard $\Lambda$CDM cosmology to explain the current cosmic acceleration, which is strongly indicated by measurements of type Ia supernovae, as well as other concordant observations.

Methods. We investigate observational constraints on this scenario provided by gravitational-lensing statistics using the Cosmic Lens All-Sky Survey (CLASS) lensing sample.

Results. We show that a substantial part of the parameter space of the DGP model agrees well with that of radio source gravitational lensing sample.

Conclusions. In the flat case, $\Omega_{\rm K}=0$, the likelihood is maximized, ${\cal L}={\cal L_{\rm max}}$, for $\Omega_{\rm M} = 0.30_^$. If we relax the prior on $\Omega_{\rm K}$, the likelihood peaks at $\{ \Omega_{\rm M},\Omega_{r_{\rm c}} \} \simeq {0.29, 0.12}$, slightly in the region of open models. The confidence contours are, however, elongated such that we are unable to discard any of the close, flat or open models.

## ZORA Wartung

ZORA's new graphical user interface has been launched. For further infos take a look at Open Access Blog 'New Look & Feel – ZORA goes mobile'.

Zhu, Z H; Sereno, M (2008). *Testing the DGP model with gravitational lensing statistics.* Astronomy and Astrophysics, 487(3):831-835.

## Abstract

Aims. The self-accelerating braneworld model (DGP) appears to provide a simple alternative to the standard $\Lambda$CDM cosmology to explain the current cosmic acceleration, which is strongly indicated by measurements of type Ia supernovae, as well as other concordant observations.

Methods. We investigate observational constraints on this scenario provided by gravitational-lensing statistics using the Cosmic Lens All-Sky Survey (CLASS) lensing sample.

Results. We show that a substantial part of the parameter space of the DGP model agrees well with that of radio source gravitational lensing sample.

Conclusions. In the flat case, $\Omega_{\rm K}=0$, the likelihood is maximized, ${\cal L}={\cal L_{\rm max}}$, for $\Omega_{\rm M} = 0.30_^$. If we relax the prior on $\Omega_{\rm K}$, the likelihood peaks at $\{ \Omega_{\rm M},\Omega_{r_{\rm c}} \} \simeq {0.29, 0.12}$, slightly in the region of open models. The confidence contours are, however, elongated such that we are unable to discard any of the close, flat or open models.

## Citations

## Altmetrics

## Downloads

## Additional indexing

Item Type: | Journal Article, refereed, original work |
---|---|

Communities & Collections: | 07 Faculty of Science > Institute for Computational Science |

Dewey Decimal Classification: | 530 Physics |

Language: | English |

Date: | September 2008 |

Deposited On: | 06 Mar 2009 11:21 |

Last Modified: | 05 Apr 2016 13:07 |

Publisher: | EDP Sciences |

ISSN: | 0004-6361 |

Free access at: | Publisher DOI. An embargo period may apply. |

Publisher DOI: | 10.1051/0004-6361:200809386 |

Related URLs: | http://arxiv.org/abs/0804.2917 |

## Download

Filetype:
PDF (Verlags-PDF)
- Registered users only
Size: 1MB View at publisher | ||

| Content: Accepted Version Filetype: PDF Size: 103kB |

TrendTerms displays relevant terms of the abstract of this publication and related documents on a map. The terms and their relations were extracted from ZORA using word statistics. Their timelines are taken from ZORA as well. The bubble size of a term is proportional to the number of documents where the term occurs. Red, orange, yellow and green colors are used for terms that occur in the current document; red indicates high interlinkedness of a term with other terms, orange, yellow and green decreasing interlinkedness. Blue is used for terms that have a relation with the terms in this document, but occur in other documents.

You can navigate and zoom the map. Mouse-hovering a term displays its timeline, clicking it yields the associated documents.